‘Surviving’ videogame production is tenuous as is, but when considering workers’ experiences with a number of moderating problems, especially loneliness and isolation, suddenly, ‘surviving’ production isn’t just about getting through the long hours: it’s about finding kindred spirits and likeminded confidants. In this project, I examine how the use of institutional ethnography (Smith, 2005) and feminist ethnography (Visweswaran, 1994) can facilitate new ways of understanding the situated, embodied experiences of workers in the videogame industry. In recounting their stories, I position this project as the beginning of a ‘de-walling’ in videogame production. I interviewed 6 current videogame production workers situated in triple-A production spaces about their experience with unionization: who they see (or don’t see) pushing for unionization, inclusive/exclusive language choices, and their thoughts on the process altogether. Unlike union initiatives in the past, videogame production has yet to thoroughly define itself, and its representative bounds. Until that work is done, it will be impossible to imagine a unionization effort that is not omitting certain sectors of the production process, and the bodies labouring in those sectors. This project borrows work from my dissertation to assist in that definitional process. Once this work is done, the situated, embodied experiences my informants have shared with me can be used as proverbial lights in the dark for workers who share my informants’ experiences with loneliness, isolation, and feeling left out of unionization talks.

Bioethicists and humanistic researchers alike have long been concerned over the effects of unchecked industry money on biomedical cultures. Corporate-funded clinical trials, free lunches, free travel, and industry honoraria for scientists have been shown to adversely affect the integrity of biomedical research. Despite the broad recognition of these hazards, efforts to address them have largely been limited to disclosure requirements and related training. Current standards require clinical researchers to report certain conflicts of interest alongside published scholarship. Unfortunately, a growing body of evidence indicates that disclosure statements often result in unintended and pernicious effects. For example, they have been shown to cause audiences to extend more trust to those holding conflicts of interest, as disclosure provides an opportunity to display both honesty and expertise. Conflict disclosure can also lead to "moral licensing," a phenomenon whereby those who disclose conflicts become unduly confident in their objectivity because transparency obligations have been fulfilled. Finally, disclosure requirements embody some of the most concerning aspects of neoliberal oversight in that they focus attention on individual behavior rather than cultural conditions. Ultimately, a significant shift in our understanding of conflicts of interest is required, and this is where the insights of digital humanities (DH) can be most beneficial. However, in order for this kind of theoretically-informed relational network modeling to be of use to humanities research, scholars need effective and efficient tools to transform the dense prose of disclosure statements, financial reports, or database outputs into useable visualizations. This is precisely what the Transparency to Visualization (T2V) tool is designed to do. One of the central intellectual projects in the humanities over the past several decades has been to develop robust theoretical accounts of power and influence within relational assemblages. Extending this project technologically, DH researchers have developed a robust and rapidly growing set of network analysis and visualization tools. Indeed, in recent years DH researchers have leveraged network visualization algorithms to create impressive accounts of citation structures, social media networks, archival letters, and so on. However, despite the impressive proliferation of network visualization technologies, preparing humanistic data for network visualization can be a significant challenge. While some data sets, like social media repositories, have the kind of rich structured metadata that can support rapid visualization, creating networks from more traditional textual data sets can present significant challenges, especially at scale. The T2V project team, which includes scholars in DH, rhetoric, and technical communication, is working to address these challenges through the development of a DH tool that is capable of extracting relational data out of prose. Our toolkit combines natural language processing, machine-learning enhanced named-entity recognition, and regular expressions to create a script that "reads" biomedical disclosure statements for economic relationships and prepares extracted data for subsequent visualization. The proposed presentation will explain and demonstrate the toolkit while reflecting on how these kinds of resistant DH projects can contribute positively to issues of social concern.

BART has considered using financial recognition software to ensure the ‘safety’ of its passengers. The NYPD has been collaborating on a similar software program for its subway stations with IBM—who made waves recently with its ‘Diversity in Faces’ trial, where its facial recognition software ‘[used] a custom AI to analyze and describe [a] collection of 99.2 million photos’ taken from online photo platform Flickr, without said platform’s consent. Facial recognition software—a biometric technology that is used to identify or verify a person by comparing facial attributes to some present metric—is increasingly the talk of the town, as questions of whether the technology represents an invasion of privacy—particularly in the context of policing and security. As the technology develops and is increasingly implemented, avoidance is increasingly unfeasible. Walking to the store, taking the train, existing, really, as a subject in public social spaces will increasingly become fraught with the threat of surveillance which can identify down to the most ‘unplugged’ of individuals. Who will control these technologies? And who will these entities answer to? As most of the technologies become centralized in the hands of security authorities, it is clear that this technology will revolutionize the historical practice of regulating entry and access to public spaces and spheres. My project takes these mitigating circumstances as an entry point towards an analysis of the CV Dazzle Project, towards figurations of ‘femme sousveillance’. CV Dazzle—named after naval camouflage used during WWII—is the brainchild of Adam Harvey, a content designer and make-up artist. The open-source project, consisting of fantastical facial make-up and concept templates and code, is designed to offer ‘looks’ which can frustrate facial recognition software and provide make-up artists with testers with which to test their own designs. The project, part radical praxis and artistic avenue, pushes the boundaries of technology and artistry in an age of mass surveillance; in being open source (both in providing facial templates and technological tools through which to identify optimal facial designs), it extends the potentially liberatory technique of ‘excessiveness’ to individuals not already primed in spaces that allow them to interact with these tools (in a way that is economically and materially safe). In focusing on the realm of make-up and facial transformation (many templates have additional body modification aspects, like extended bangs, jewel designs, etc.), the ‘surface excess’ that the templates exemplify perform a kind of ‘femme sousveillance’, a ‘looking back’ that is predicated on an ‘excessive’ performance of (what could be considered) the ‘femme’. My exercise brings together these threads to think about the role of open source projects and artistic potential in the development of fantastical resistances toward overarching systems of surveillance that threaten vulnerable populations, an exercise I feel is perfectly situated for the discussions to take place at Digital Frontiers 2019.